Abstract
With the advent of Web 2.0, tagging has become a common practice over the Web and a valuable source of metadata that has been increasingly exploited for resource classification and retrieval. Several research efforts have been conducted in the recent years to improve the productivity of user created tags by providing them with a proper structure and semantics. Also several approaches have been proposed to add implicit tags to resources both by analyzing the media and measuring the physiological and physical signals produced by the humans interacting with the media. This paper discusses the application of Semantic Web technologies to foster Affective Tagging. In particular, a human emotion ontology is proposed to standardize the main emotion models and map together different representations. In addition, public knowledge bases exposed as Linked Data can be exploited not only to disambiguate words and concepts, overcoming some of the main issues related to the use of natural language, but also to reveal the affective valence of such tags.
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Grassi, M., Piazza, F. (2012). Ontology-Based Semantic Affective Tagging. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_44
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DOI: https://doi.org/10.1007/978-3-642-31346-2_44
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